A method for increasing expressivity of Gene Ontology annotations using a compositional approach.

Rachael P Huntley, Midori A Harris, Yasmin Alam-Faruque, Judith A Blake, Seth Carbon, Heiko Dietze, Emily C Dimmer, Rebecca E Foulger, David P Hill, Varsha K Khodiyar, Antonia Lock, Jane Lomax, Ruth C Lovering, Prudence Mutowo-Meullenet, Tony Sawford, Kimberly Van Auken, Valerie Wood, Christopher J Mungall

Journal: BMC bioinformatics 2014;15():155

PMID: 24885854

Abstract

BACKGROUND

The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations.

RESULTS

The GO Consortium has introduced annotation extensions that enable manually curated GO annotations to capture additional contextual details. Extensions represent effector-target relationships such as localization dependencies, substrates of protein modifiers and regulation targets of signaling pathways and transcription factors as well as spatial and temporal aspects of processes such as cell or tissue type or developmental stage. We describe the content and structure of annotation extensions, provide examples, and summarize the current usage of annotation extensions.

CONCLUSIONS

The additional contextual information captured by annotation extensions improves the utility of functional annotation by representing dependencies between annotations to terms in the different ontologies of GO, external ontologies, or an organism's gene products. These enhanced annotations can also support sophisticated queries and reasoning, and will provide curated, directional links between many gene products to support pathway and network reconstruction.

Address: Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. [email protected].
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